Satellite Detection of Moving Vessels in Marine Environments


  • Natalie Fridman ImageSat International
  • Doron Amir ImageSat International
  • Yinon Douchan ImageSat International
  • Noa Agmon Bar-Ilan University



There is a growing need for coverage of large maritime areas, mainly in the exclusive economic zone (EEZ). Due to the difficulty of accessing such large areas, the use of satellite based sensors is the most efficient and cost-effective way to perform this task. Vessel behavior prediction is a necessary ability for detection of moving vessels with satellite imagery. In this paper we present an algorithm for selection of the best satellite observation window to detect a moving object. First, we describe a model for vessel behavior prediction and compare its performance to two base models. We use real marine traffic data (AIS) to compare their ability to predict vessel behavior in a time frame of between 1–24 hours. Then, we present a KINGFISHER, maritime intelligence system which uses our algorithm to track suspected vessels with satellite sensor. We also present the results of the algorithm in operational scenarios of the KINGFISHER.




How to Cite

Fridman, N., Amir, D., Douchan, Y., & Agmon, N. (2019). Satellite Detection of Moving Vessels in Marine Environments. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 9452-9459.



IAAI Technical Track: Emerging Papers